%0 Journal Article
%T Graph-Based Term Weighting for Document Ranking<br>基于图的特征词权重算法及其在文档排序中的应用
%A HUANG Yun
%A HONG Jia-Ming
%A YAN Yi-Ming
%A <br>黄云
%A 洪佳明
%A 颜一鸣
%J 计算机系统应用
%D 2012
%I 
%X The core work of information retrieval including document classification and ranking operations, how to effectively compute the term weight of every document is one of a key technology. Use of the word relationship to create a text graph for each document, based on the idea of the importance of interaction between adjacent words, combining the characteristics of the word document word frequency characteristics, we iteratively compute weighting of each word. Further combining the global properties of text graph, such as density, we could rank the results of information retrieval. Experiments confirmed that the algorithm in standard data sets with good results.
%K text graph
%K co-occurrence relation
%K document ranking
%K term weight<br>文本图
%K 共现关系
%K 文档排序
%K 特征词权重
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=57C6AD9B0ADA0537BD4B8542D2258D36&yid=99E9153A83D4CB11&vid=659D3B06EBF534A7&iid=B31275AF3241DB2D&sid=CEC789B3C68C3BB3&eid=50E5FD87D4D6081F&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=7